Person Identification From Audio and Visual Aesthetics
Date
2021-11
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Abstract
In recent years, the trend that allowed for person identiļ¬cation based on behavior rather than physical traits to emerge as a growing research domain. Its application spans areas such as online education, e-commerce, e-communication, human-computer interaction, robotics, and biometric security. The expression of opinions is an example of online behavior, that is commonly shared through the liking of images or music. A person's aesthetic preference involves using a person's sense of fondness to experienced stimulus. This thesis examines for the first time aesthetic preference as a biometric trait. It then establishes the efficacy of a combined multi-modal approach to person identification using aesthetic preference. The potency of this approach is tested on a proprietary dataset.
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Keywords
Machine Learning, Deep Learning, Behavioral Biometrics, Biometric Security, Visual Aesthetics, Audio Aesthetics, Pattern Recognition
Citation
Sieu, B. (2021). Person identification from audio and visual aesthetics (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.